Discover new connections between published research papers with Connected Papers, a free academic search tool that analyzes paper text and visualizes connections in an interactive graph.
Connected Papers is a free academic search tool designed to help researchers discover new connections between published research papers. It works by analyzing the full text of a seed research paper provided by the user to identify related papers based on similarity of text. The tool then visualizes the connections between the seed paper and related papers in an interactive graph.
To use Connected Papers, a researcher starts by providing the details (title, authors, etc.) or a PDF of a published seed research paper they are interested in. Connected Papers analyzes the full text of this seed paper to find related papers based on textual similarity. It then displays an interactive graph with nodes representing papers and edges representing the textual connections between them.
By clicking on any node in the graph, the user can explore papers related to the seed paper or any other paper in their results. As they explore, new papers and connections are added to the graph automatically by the tool. Researchers can discover papers relevant to their work that they may have missed using traditional search methods.
Key features of Connected Papers include:
By leveraging machine learning and natural language processing, Connected Papers allows researchers to quickly visualize and explore connections between research papers related to their work. It serves as a discovery tool to find relevant papers a researcher may have missed with database searches.
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